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For dispersion under identical hydrodynamic conditions, the model predicts faster erosion for larger agglomerates.
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Although our model predicts fastest development of the insect between 27 30°C, there is clear trade-off between development time and reproductive success as previously shown for other insects [43].
Although the sea urchin Strongylocentrotus franciscanus has a longer generation time, a population genetic model predicted faster rates of adaptive evolution in sea urchins compared with mussels (Mytilus trossolus) because larvae of the latter possessed lower levels of additive genetic variance.
The comparison shows that the Darcy model over estimates the mass fraction of aqueous and adsorbed species B and underestimates the mass fractions of species A. The Darcy-scale model also predicts faster transport of species A and B through the system than the pore-scale model.
The model thus predicts fast oxidation during a brief initial period followed by a slow-oxidation one.
The proposed 2-D model predicts a faster damage propagation than the 1-D models.
These tails indicate DNA segments where the model predicts much faster or slower replication than observed in the experiments.
Somewhat surprisingly, the model predicts the fastest decline for both the Random and Household mechanisms.
Unlike previous attempts, our model does predict faster RTs accompanied by higher thresholds, under specific circumstances.
The model predicts that the fastest viral decay rate (the maximum of the curve in Figure 2B) is always at the same level of depletion of CD4+ T cells (Figure 2C).
The simulation results were generally satisfactory, although the model predicted slightly faster consumption of both substrates and small overprediction of biomass production throughout most of the batch.
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